An artifacts removal post-processing for epiphyseal region-of-interest (EROI) localization in automated bone age assessment (BAA)
Background Segmentation is the most crucial part in the computer-aided bone age assessment. A well-known type of segmentation performed in the system is adaptive segmentation. While providing better result than global thresholding method, the adaptive segmentation produces a lot of unwanted noise th...
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my.utm.447232017-08-30T04:34:50Z http://eprints.utm.my/id/eprint/44723/ An artifacts removal post-processing for epiphyseal region-of-interest (EROI) localization in automated bone age assessment (BAA) Hum, Yan Chai Lai, Khin Wee Tan, Tian Swee Shaikh Salleh, Sheikh-Hussain Lim, Yee Chea CC Archaeology Background Segmentation is the most crucial part in the computer-aided bone age assessment. A well-known type of segmentation performed in the system is adaptive segmentation. While providing better result than global thresholding method, the adaptive segmentation produces a lot of unwanted noise that could affect the latter process of epiphysis extraction. Methods A proposed method with anisotropic diffusion as pre-processing and a novel Bounded Area Elimination (BAE) post-processing algorithm to improve the algorithm of ossification site localization technique are designed with the intent of improving the adaptive segmentation result and the region-of interest (ROI) localization accuracy. Results The results are then evaluated by quantitative analysis and qualitative analysis using texture feature evaluation. The result indicates that the image homogeneity after anisotropic diffusion has improved averagely on each age group for 17.59%. Results of experiments showed that the smoothness has been improved averagely 35% after BAE algorithm and the improvement of ROI localization has improved for averagely 8.19%. The MSSIM has improved averagely 10.49% after performing the BAE algorithm on the adaptive segmented hand radiograph. Conclusions The result indicated that hand radiographs which have undergone anisotropic diffusion have greatly reduced the noise in the segmented image and the result as well indicated that the BAE algorithm proposed is capable of removing the artifacts generated in adaptive segmentation. BioMed Central Ltd 2011 Article PeerReviewed Hum, Yan Chai and Lai, Khin Wee and Tan, Tian Swee and Shaikh Salleh, Sheikh-Hussain and Lim, Yee Chea (2011) An artifacts removal post-processing for epiphyseal region-of-interest (EROI) localization in automated bone age assessment (BAA). BioMedical Engineering OnLine, 10 (87). pp. 1-22. ISSN 1475-925X |
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CC Archaeology Hum, Yan Chai Lai, Khin Wee Tan, Tian Swee Shaikh Salleh, Sheikh-Hussain Lim, Yee Chea An artifacts removal post-processing for epiphyseal region-of-interest (EROI) localization in automated bone age assessment (BAA) |
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Background Segmentation is the most crucial part in the computer-aided bone age assessment. A well-known type of segmentation performed in the system is adaptive segmentation. While providing better result than global thresholding method, the adaptive segmentation produces a lot of unwanted noise that could affect the latter process of epiphysis extraction. Methods A proposed method with anisotropic diffusion as pre-processing and a novel Bounded Area Elimination (BAE) post-processing algorithm to improve the algorithm of ossification site localization technique are designed with the intent of improving the adaptive segmentation result and the region-of interest (ROI) localization accuracy. Results The results are then evaluated by quantitative analysis and qualitative analysis using texture feature evaluation. The result indicates that the image homogeneity after anisotropic diffusion has improved averagely on each age group for 17.59%. Results of experiments showed that the smoothness has been improved averagely 35% after BAE algorithm and the improvement of ROI localization has improved for averagely 8.19%. The MSSIM has improved averagely 10.49% after performing the BAE algorithm on the adaptive segmented hand radiograph. Conclusions The result indicated that hand radiographs which have undergone anisotropic diffusion have greatly reduced the noise in the segmented image and the result as well indicated that the BAE algorithm proposed is capable of removing the artifacts generated in adaptive segmentation. |
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Article |
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Hum, Yan Chai Lai, Khin Wee Tan, Tian Swee Shaikh Salleh, Sheikh-Hussain Lim, Yee Chea |
author_facet |
Hum, Yan Chai Lai, Khin Wee Tan, Tian Swee Shaikh Salleh, Sheikh-Hussain Lim, Yee Chea |
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Hum, Yan Chai |
title |
An artifacts removal post-processing for epiphyseal region-of-interest (EROI) localization in automated bone age assessment (BAA) |
title_short |
An artifacts removal post-processing for epiphyseal region-of-interest (EROI) localization in automated bone age assessment (BAA) |
title_full |
An artifacts removal post-processing for epiphyseal region-of-interest (EROI) localization in automated bone age assessment (BAA) |
title_fullStr |
An artifacts removal post-processing for epiphyseal region-of-interest (EROI) localization in automated bone age assessment (BAA) |
title_full_unstemmed |
An artifacts removal post-processing for epiphyseal region-of-interest (EROI) localization in automated bone age assessment (BAA) |
title_sort |
artifacts removal post-processing for epiphyseal region-of-interest (eroi) localization in automated bone age assessment (baa) |
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BioMed Central Ltd |
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2011 |
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http://eprints.utm.my/id/eprint/44723/ |
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